ROC Curves and Precision-Recall Curves for Imbalanced Classification
Por um escritor misterioso
Last updated 02 janeiro 2025
Most imbalanced classification problems involve two classes: a negative case with the majority of examples and a positive case with a minority of examples. Two diagnostic tools that help in the interpretation of binary (two-class) classification predictive models are ROC Curves and Precision-Recall curves. Plots from the curves can be created and used to understand […]
Complete Guide to Understanding Precision and Recall Curves
Applications of Different Parts of an ROC Curve, by Prince Grover
Why Can't I just Use the ROC Curve?, by Chris Kuo/Dr. Dataman, Dataman in AI
Handling Class Imbalance with R and Caret - Caveats when using the AUC
A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms, BMC Medical Informatics and Decision Making
PDF] The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets
PDF] PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R
Precision - Recall Curve, a Different View of Imbalanced Classifiers – Sin-Yi Chou – Data Science Enthusiast
Understanding AUC — ROC and Precision-Recall Curves, by Maria Gusarova
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